In this paper, a new method for face localization in
color images, which is based on co-evolutionary systems, is
introduced. The proposed method uses a co-evolutionary
system to locate the eyes in a face image. The used coevolutionary
system involves two genetic algorithm models.
The first GA model searches for a solution in the given
environment, and the second GA model searches for useful
genetic information in the first GA model. In the next step, by
using the location of eyes in image the parameters of face's
bounding ellipse (center, orientation, major and minor axis)
are computed. To evaluate and compare the proposed method
with other methods, high order Pseudo Zernike Moments
(PZM) are utilized to produce feature vectors and a Radial
Basis Function (RBF) neural network is used as the classifier.
Simulation results indicate that the speed and accuracy of the
new system using the proposed face localization method which
uses a co-evolutionary approach is higher than the system
proposed in [10].
Keywords-face localization; genetic algorithm; coevolutionary

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